{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:6B352G2XCW7CVFON6HBQD6RYRL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"21380dfa833b0cb7f7d37dac6cf837ee5cec882da8944e1a3c6358e050cb82e9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-06-21T16:42:20Z","title_canon_sha256":"6169114cebd80813f0ae9d335734313f127472cdd86dcb90df91247b678a92ab"},"schema_version":"1.0","source":{"id":"1606.06650","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.06650","created_at":"2026-05-18T01:12:09Z"},{"alias_kind":"arxiv_version","alias_value":"1606.06650v1","created_at":"2026-05-18T01:12:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.06650","created_at":"2026-05-18T01:12:09Z"},{"alias_kind":"pith_short_12","alias_value":"6B352G2XCW7C","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"6B352G2XCW7CVFON","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"6B352G2X","created_at":"2026-05-18T12:30:01Z"}],"graph_snapshots":[{"event_id":"sha256:068a41d9fdfb916a44472e71f0cbad9a61f5e8f2801d7a6b5d7c71677a1b653a","target":"graph","created_at":"2026-05-18T01:12:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi-automated setup, the user annotates some slices in the volume to be segmented. The network learns from these sparse annotations and provides a dense 3D segmentation. (2) In a fully-automated setup, we assume that a representative, sparsely annotated training set exists. Trained on this data set, the network densely segments new volumetric images. The proposed network extends the previous u-net architecture from Ronn","authors_text":"Ahmed Abdulkadir, Olaf Ronneberger, \\\"Ozg\\\"un \\c{C}i\\c{c}ek, Soeren S. Lienkamp, Thomas Brox","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-06-21T16:42:20Z","title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.06650","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:49003e0f0fe005ad5ad3235a769ab0d8c686b1ce9195898d93ec695942bbd6d4","target":"record","created_at":"2026-05-18T01:12:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"21380dfa833b0cb7f7d37dac6cf837ee5cec882da8944e1a3c6358e050cb82e9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-06-21T16:42:20Z","title_canon_sha256":"6169114cebd80813f0ae9d335734313f127472cdd86dcb90df91247b678a92ab"},"schema_version":"1.0","source":{"id":"1606.06650","kind":"arxiv","version":1}},"canonical_sha256":"f077dd1b5715be2a95cdf1c301fa388aec91de7640fe5c0fd9876eacc5db4438","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f077dd1b5715be2a95cdf1c301fa388aec91de7640fe5c0fd9876eacc5db4438","first_computed_at":"2026-05-18T01:12:09.047272Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:12:09.047272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KrQ2alrMvTKDgcweucZTLNT247Js6Kiw7W9wChYiLEPlJF+2N2oYaebYfU8KPT/KVCFmQYtN9KPto3467UxFCw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:12:09.047695Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.06650","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:49003e0f0fe005ad5ad3235a769ab0d8c686b1ce9195898d93ec695942bbd6d4","sha256:068a41d9fdfb916a44472e71f0cbad9a61f5e8f2801d7a6b5d7c71677a1b653a"],"state_sha256":"3558d3e06bd4ddc710231f895cb6e859f4733e60a16e455e0f6bf6121e4f13cb"}